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feat: improve type generation with discriminated union support (#21)
- Pull latest AdCP schemas (v1.0.0) with new destination and deployment types - Add discriminated union generation for oneOf schemas with type discriminators - Handle const fields for proper Literal types in discriminators - Add missing ActivationKey type alias for deployment schema Changes to type generation: - New `generate_discriminated_union()` function handles oneOf schemas - Automatically detects discriminator field (type) and generates typed variants - Example: Destination = PlatformDestination | AgentDestination - Each variant gets proper Literal["platform"] | Literal["agent"] type New types added: - PlatformDestination / AgentDestination (discriminated union) - PlatformDeployment / AgentDeployment (discriminated union) - ActivationKey type alias Improved existing types: - BrandManifestRef now discriminated union (was Any) - StartTiming now discriminated union (was Any) - PricingOption now discriminated union (was Any) All tests pass with Python 3.11+. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-authored-by: Claude <noreply@anthropic.com>
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‎schemas/cache/1.0.0/deployment.json‎

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{
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"$schema": "http://json-schema.org/draft-07/schema#",
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"$id": "/schemas/v1/core/deployment.json",
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"title": "Deployment",
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"description": "A signal deployment to a specific destination platform with activation status and key",
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"oneOf": [
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{
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"type": "object",
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"properties": {
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"type": {
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"const": "platform",
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"description": "Discriminator indicating this is a platform-based deployment"
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},
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"platform": {
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"type": "string",
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"description": "Platform identifier for DSPs"
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},
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"account": {
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"type": "string",
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"description": "Account identifier if applicable"
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},
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"is_live": {
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"type": "boolean",
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"description": "Whether signal is currently active on this destination"
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},
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"activation_key": {
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"$ref": "activation-key.json",
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"description": "The key to use for targeting. Only present if is_live=true AND requester has access to this destination."
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},
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"estimated_activation_duration_minutes": {
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"type": "number",
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"description": "Estimated time to activate if not live, or to complete activation if in progress",
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"minimum": 0
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},
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"deployed_at": {
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"type": "string",
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"format": "date-time",
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"description": "Timestamp when activation completed (if is_live=true)"
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}
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},
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"required": [
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"type",
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"platform",
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"is_live"
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],
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"additionalProperties": false
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},
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{
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"type": "object",
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"properties": {
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"type": {
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"const": "agent",
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"description": "Discriminator indicating this is an agent URL-based deployment"
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},
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"agent_url": {
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"type": "string",
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"format": "uri",
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"description": "URL identifying the destination agent"
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},
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"account": {
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"type": "string",
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"description": "Account identifier if applicable"
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},
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"is_live": {
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"type": "boolean",
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"description": "Whether signal is currently active on this destination"
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},
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"activation_key": {
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"$ref": "activation-key.json",
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"description": "The key to use for targeting. Only present if is_live=true AND requester has access to this destination."
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},
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"estimated_activation_duration_minutes": {
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"type": "number",
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"description": "Estimated time to activate if not live, or to complete activation if in progress",
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"minimum": 0
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},
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"deployed_at": {
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"type": "string",
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"format": "date-time",
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"description": "Timestamp when activation completed (if is_live=true)"
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}
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},
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"required": [
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"type",
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"agent_url",
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"is_live"
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],
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"additionalProperties": false
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}
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]
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}

‎schemas/cache/1.0.0/destination.json‎

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{
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"$schema": "http://json-schema.org/draft-07/schema#",
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"$id": "/schemas/v1/core/destination.json",
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"title": "Destination",
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"description": "A destination platform where signals can be activated (DSP, sales agent, etc.)",
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"oneOf": [
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{
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"type": "object",
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"properties": {
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"type": {
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"const": "platform",
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"description": "Discriminator indicating this is a platform-based destination"
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},
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"platform": {
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"type": "string",
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"description": "Platform identifier for DSPs (e.g., 'the-trade-desk', 'amazon-dsp')"
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},
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"account": {
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"type": "string",
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"description": "Optional account identifier on the platform"
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}
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},
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"required": [
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"type",
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"platform"
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],
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"additionalProperties": false
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},
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{
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"type": "object",
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"properties": {
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"type": {
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"const": "agent",
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"description": "Discriminator indicating this is an agent URL-based destination"
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},
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"agent_url": {
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"type": "string",
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"format": "uri",
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"description": "URL identifying the destination agent (for sales agents, etc.)"
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},
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"account": {
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"type": "string",
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"description": "Optional account identifier on the agent"
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}
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},
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"required": [
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"type",
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"agent_url"
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],
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"additionalProperties": false
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}
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]
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}

‎scripts/generate_models_simple.py‎

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@@ -66,6 +66,102 @@ def escape_string_for_python(text: str) -> str:
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return text.strip()
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def generate_discriminated_union(schema: dict, base_name: str) -> str:
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"""
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Generate Pydantic models for a discriminated union (oneOf with type discriminator).
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Creates a base model for each variant and a union type for the parent.
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For example, Destination = PlatformDestination | AgentDestination
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"""
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lines = []
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# Add schema description as a comment
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if "description" in schema:
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desc = escape_string_for_python(schema["description"])
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lines.append(f"# {desc}")
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lines.append("")
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variant_names = []
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# Generate a model for each variant in oneOf
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for i, variant in enumerate(schema.get("oneOf", [])):
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# Try to get discriminator value for better naming
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discriminator_value = None
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if "properties" in variant and "type" in variant["properties"]:
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type_prop = variant["properties"]["type"]
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if "const" in type_prop:
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discriminator_value = type_prop["const"]
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# Generate variant name
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if discriminator_value:
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variant_name = f"{discriminator_value.capitalize()}{base_name}"
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else:
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variant_name = f"{base_name}Variant{i+1}"
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variant_names.append(variant_name)
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# Generate the variant model
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lines.append(f"class {variant_name}(BaseModel):")
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# Add description if available
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if "description" in variant:
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desc = variant["description"].replace("\\", "\\\\").replace('"""', '\\"\\"\\"')
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desc = desc.replace("\n", " ").replace("\r", "")
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desc = re.sub(r"\s+", " ", desc).strip()
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lines.append(f' """{desc}"""')
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lines.append("")
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# Add properties
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if "properties" in variant and variant["properties"]:
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for prop_name, prop_schema in variant["properties"].items():
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safe_name, needs_alias = sanitize_field_name(prop_name)
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prop_type = get_python_type(prop_schema)
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desc = prop_schema.get("description", "")
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if desc:
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desc = escape_string_for_python(desc)
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is_required = prop_name in variant.get("required", [])
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if is_required:
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if desc and needs_alias:
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lines.append(
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f' {safe_name}: {prop_type} = Field(alias="{prop_name}", description="{desc}")'
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)
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elif desc:
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lines.append(f' {safe_name}: {prop_type} = Field(description="{desc}")')
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elif needs_alias:
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lines.append(f' {safe_name}: {prop_type} = Field(alias="{prop_name}")')
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else:
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lines.append(f" {safe_name}: {prop_type}")
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else:
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if desc and needs_alias:
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lines.append(
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f' {safe_name}: {prop_type} | None = Field(None, alias="{prop_name}", description="{desc}")'
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)
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elif desc:
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lines.append(
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f' {safe_name}: {prop_type} | None = Field(None, description="{desc}")'
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)
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elif needs_alias:
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lines.append(
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f' {safe_name}: {prop_type} | None = Field(None, alias="{prop_name}")'
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)
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else:
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lines.append(f" {safe_name}: {prop_type} | None = None")
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else:
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lines.append(" pass")
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lines.append("")
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lines.append("")
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# Create union type
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union_type = " | ".join(variant_names)
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lines.append(f"# Union type for {schema.get('title', base_name)}")
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lines.append(f"{base_name} = {union_type}")
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return "\n".join(lines)
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def generate_model_for_schema(schema_file: Path) -> str:
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"""Generate Pydantic model code for a single schema inline."""
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with open(schema_file) as f:
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# Start with model name
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model_name = snake_to_pascal(schema_file.stem)
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# Check if this is a oneOf discriminated union
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if "oneOf" in schema and "properties" not in schema:
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return generate_discriminated_union(schema, model_name)
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# Check if this is a simple type alias (enum or primitive type without properties)
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if "properties" not in schema:
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# This is a type alias, not a model class
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ref = schema["$ref"]
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return snake_to_pascal(ref.replace(".json", ""))
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# Handle const (discriminator values)
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if "const" in schema:
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const_value = schema["const"]
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if isinstance(const_value, str):
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return f'Literal["{const_value}"]'
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return f"Literal[{const_value}]"
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schema_type = schema.get("type")
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if schema_type == "string":
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"protocol-envelope.json",
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"response.json",
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"promoted-products.json",
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"destination.json",
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"deployment.json",
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# Enum types (need type aliases)
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"channels.json",
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"delivery-type.json",
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"",
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"# These types are referenced in schemas but don't have schema files",
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"# Defining them as type aliases to maintain type safety",
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"ActivationKey = dict[str, Any]",
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"PackageRequest = dict[str, Any]",
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"PushNotificationConfig = dict[str, Any]",
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"ReportingCapabilities = dict[str, Any]",

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